Biomedical Nanocenter, School of Life Science, Inner Mongolia Agricultural University, Hohhot, China.
Pharmacy Laboratory, Inner Mongolia International Mongolian Hospital, Hohhot, China.
J Food Biochem. 2022 Oct;46(10):e14338. doi: 10.1111/jfbc.14338. Epub 2022 Aug 7.
Considering that natural products as tyrosinase inhibitors are considered to be safe, with little or no toxic side effects and friendly to the environment, it is urgent to develop a new recognition strategy for natural tyrosinase inhibitors. In current study, an integrated computational analysis was conducted on Cys-containing dipeptides with high tyrosinase inhibitory activity. Firstly, molecular fingerprint similarity (FS) clustering analysis was performed on the target molecule using machine learning. Secondly, genetic algorithm was used to construct two kinds of highly accurate QSAR models (R = .978 and .984, respectively) with Cys at C-terminal and N-terminal. Finally, three novel natural candidate inhibitors (NP1, NP2, NP3) were discovered using Molnatsim natural product cluster library, automated screening process and QSAR based on the maximum common substructure (MCS) algorithm, their IC were 260.96, 3.37 and 0.05 μm/mol. Pharmacokinetic predictions showed that NP2 and NP3 had high Bioavailability Score (BS) and Gastrointestinal (GI) absorption, and molecular dynamics simulations further validated the stability of these novel natural candidate inhibitors in binding to tyrosinase. In conclusion, our results provide new ideas for discovering new activities of natural products, and provide an accurate QSAR model for developing novel tyrosinase inhibitors based on MCS Cys-containing dipeptides. PRACTICAL APPLICATIONS: Tyrosinase is related to the occurrence of diseases such as excessive melanin deposition such as freckles and chloasma, and studies have shown that neurodegeneration associated with Parkinson's disease and Huntington's disease is also related. In addition, enzymatic browning on the surface of fresh fruit and vegetable slices will shorten the shelf life and affect their quality. Therefore, screening, designing and developing efficient tyrosinase inhibitors is very important in the fields of medicine, cosmetics, food and so on.
考虑到天然产物作为酪氨酸酶抑制剂被认为是安全的,具有很少或没有毒副作用,并且对环境友好,因此迫切需要开发一种新的天然酪氨酸酶抑制剂识别策略。在当前的研究中,对具有高酪氨酸酶抑制活性的含半胱氨酸二肽进行了综合计算分析。首先,使用机器学习对半胱氨酸二肽的目标分子进行分子指纹相似性(FS)聚类分析。其次,使用遗传算法构建了两种高精度 QSAR 模型(R 分别为.978 和.984),C 末端和 N 末端均为半胱氨酸。最后,使用 Molnatsim 天然产物聚类库、自动筛选过程和基于最大公共子结构(MCS)算法的 QSAR 发现了三种新型天然候选抑制剂(NP1、NP2、NP3),其 IC 分别为 260.96、3.37 和 0.05μm/mol。药代动力学预测表明 NP2 和 NP3 具有较高的生物利用度评分(BS)和胃肠道(GI)吸收,分子动力学模拟进一步验证了这些新型天然候选抑制剂与酪氨酸酶结合的稳定性。总之,我们的研究结果为发现天然产物的新活性提供了新的思路,并为基于 MCS 含半胱氨酸二肽开发新型酪氨酸酶抑制剂提供了准确的 QSAR 模型。实际应用:酪氨酸酶与雀斑和黄褐斑等黑色素过度沉积等疾病的发生有关,研究表明,与帕金森病和亨廷顿病相关的神经退行性变也与它有关。此外,新鲜水果和蔬菜切片表面的酶促褐变会缩短货架期并影响其质量。因此,筛选、设计和开发高效的酪氨酸酶抑制剂在医学、化妆品、食品等领域非常重要。